Differential Privacy

Private Hypothesis Selection NeurIPS 2019 Private Learning Implies Online Learning: An Efficient Reduction NeurIPS 2019 Private Model Compression via Knowledge Distillation AAAI 2019 Private Stochastic Convex Optimization with Optimal Rates NeurIPS 2019 Private Testing of Distributions via Sample Permutations NeurIPS 2019 Simultaneous Private Learning of Multiple Concepts JMLR 2019 User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning NeurIPS 2019 Differentially Private Database Release via Kernel Mean Embeddings ICML 2018 Differentially Private Identity and Equivalence Testing of Discrete Distributions ICML 2018 Differentially Private k-Means with Constant Multiplicative Error NeurIPS 2018 Differentially Private Matrix Completion Revisited ICML 2018 Differentially Private Robust Low-Rank Approximation NeurIPS 2018 Differentially Private Uniformly Most Powerful Tests for Binomial Data NeurIPS 2018 Differential Privacy for Growing Databases NeurIPS 2018 Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization NeurIPS 2018 Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited NeurIPS 2018 Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising ICML 2018 INSPECTRE: Privately Estimating the Unseen ICML 2018 Local Differential Privacy for Evolving Data NeurIPS 2018 Locally Private Hypothesis Testing ICML 2018 Local Private Hypothesis Testing: Chi-Square Tests ICML 2018 Mitigating Bias in Adaptive Data Gathering via Differential Privacy ICML 2018 Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences NeurIPS 2018 Scalable Private Learning with PATE ICLR 2018 The Price of Privacy for Low-rank Factorization NeurIPS 2018